Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 115,314
2 South Dakota 102,907
3 Iowa 81,218
4 Wisconsin 80,542
5 Nebraska 77,048
6 Utah 72,959
7 Montana 68,585
8 Wyoming 68,007
9 Idaho 67,844
10 Minnesota 67,182
11 Illinois 67,110
12 Rhode Island 66,849
13 Tennessee 64,825
14 Kansas 64,757
15 Indiana 63,615
16 Arkansas 61,535
17 Nevada 60,874
18 Mississippi 60,295
19 Alabama 60,293
20 Oklahoma 60,063
21 Missouri 59,185
22 Louisiana 57,781
23 New Mexico 57,133
24 Arizona 56,142
25 Alaska 55,955
26 Florida 52,422
27 Texas 51,043
28 Kentucky 50,720
29 Colorado 50,302
30 Georgia 49,313
31 South Carolina 48,984
32 Ohio 48,141
33 Delaware 46,684
34 Michigan 46,521
35 New Jersey 45,317
36 Massachusetts 42,158
37 North Carolina 41,633
38 Connecticut 41,163
39 California 40,257
40 New York 40,138
41 Maryland 38,866
42 Pennsylvania 38,736
43 West Virginia 35,274
44 District of Columbia 35,244
45 Virginia 33,027
46 Puerto Rico 30,073
47 Washington 27,496
48 New Hampshire 22,766
49 Oregon 22,251
50 Hawaii 13,632
51 Maine 11,845
52 Vermont 9,219

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 Tennessee 1,161
2 Oklahoma 1,028
3 Indiana 1,016
4 Ohio 880
5 Texas 877
6 Nevada 875
7 South Dakota 870
8 Pennsylvania 852
9 Arizona 851
10 California 840
11 Delaware 829
12 Utah 827
13 Alaska 814
14 New Mexico 805
15 Massachusetts 763
16 Arkansas 756
17 Montana 732
18 Alabama 728
19 Mississippi 727
20 Kentucky 708
21 Wisconsin 690
22 Minnesota 685
23 South Carolina 681
24 Illinois 664
25 New Hampshire 657
26 West Virginia 655
27 Wyoming 654
28 Colorado 622
29 North Carolina 594
30 Kansas 561
31 Nebraska 555
32 Missouri 552
33 Iowa 551
34 New York 541
35 Idaho 539
36 New Jersey 527
37 Georgia 526
38 Louisiana 522
39 North Dakota 509
40 Rhode Island 494
41 Maryland 485
42 Florida 484
43 Virginia 424
44 District of Columbia 366
45 Washington 359
46 Connecticut 353
47 Michigan 347
48 Oregon 317
49 Puerto Rico 310
50 Maine 263
51 Vermont 181
52 Hawaii 94

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 1,998
2 New York 1,809
3 Massachusetts 1,646
4 North Dakota 1,519
5 Connecticut 1,504
6 Louisiana 1,466
7 Rhode Island 1,424
8 South Dakota 1,423
9 Mississippi 1,410
10 Illinois 1,210
11 Michigan 1,120
12 Iowa 1,017
13 District of Columbia 1,013
14 Arizona 1,010
15 Indiana 1,010
16 Pennsylvania 985
17 Arkansas 975
18 New Mexico 933
19 Florida 924
20 Georgia 921
21 South Carolina 920
22 Maryland 846
23 Texas 844
24 Delaware 837
25 Alabama 836
26 Nevada 826
27 Minnesota 798
28 Tennessee 791
29 Missouri 775
30 Montana 765
31 Wisconsin 746
32 Nebraska 718
33 Kansas 711
34 Colorado 691
35 Idaho 659
36 Ohio 640
37 North Carolina 558
38 Wyoming 554
39 Kentucky 549
40 West Virginia 540
41 California 532
42 Oklahoma 521
43 Virginia 516
44 New Hampshire 443
45 Washington 399
46 Puerto Rico 398
47 Utah 329
48 Oregon 274
49 Alaska 231
50 Hawaii 192
51 Maine 191
52 Vermont 152

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 South Dakota 30
2 North Dakota 21
3 New Mexico 17
4 Kansas 14
5 Minnesota 14
6 Pennsylvania 14
7 Arkansas 13
8 Illinois 12
9 Mississippi 12
10 Wyoming 12
11 Colorado 10
12 Indiana 10
13 Nevada 10
14 Tennessee 10
15 Alaska 9
16 Iowa 9
17 Michigan 9
18 Montana 9
19 Arizona 8
20 West Virginia 8
21 Nebraska 7
22 Oklahoma 7
23 South Carolina 7
24 Wisconsin 7
25 Idaho 6
26 Louisiana 6
27 Massachusetts 6
28 Texas 6
29 Maryland 5
30 New Jersey 5
31 New York 5
32 Ohio 5
33 Alabama 4
34 Florida 4
35 Kentucky 4
36 New Hampshire 4
37 Utah 4
38 California 3
39 Connecticut 3
40 Delaware 3
41 District of Columbia 3
42 Georgia 3
43 Missouri 3
44 North Carolina 3
45 Puerto Rico 3
46 Rhode Island 3
47 Vermont 3
48 Maine 2
49 Oregon 2
50 Virginia 2
51 Hawaii 1
52 Washington -1

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 235,935 1 99
Norton Kansas 211,155 2 99
Bon Homme South Dakota 206,347 3 99
Lincoln Arkansas 204,622 4 99
Buffalo South Dakota 204,383 5 99
Davidson Tennessee 78,387 503 83
Richland South Carolina 55,017 1432 54
York South Carolina 43,053 2101 33
Orange California 33,006 2538 19
Pierce Washington 25,635 2771 11

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 7,587 1 99
Jerauld South Dakota 7,452 2 99
Dickey North Dakota 6,568 3 99
Foster North Dakota 5,919 4 99
Gregory South Dakota 5,735 5 99
Richland South Carolina 755 1575 49
Davidson Tennessee 684 1723 45
York South Carolina 555 1981 36
Orange California 533 2031 35
Pierce Washington 323 2502 20

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons